What is synthetic data and how can it address AI’s privacy and copyright issues?

In today’s digital world, data and artificial intelligence (AI) are everywhere. Companies are always looking for data to train their AI systems. This search has raised concerns about privacy and copyright.

What is Synthetic Data?

Synthetic Data is “fake” data created by computers. It looks like real data but doesn’t include any personal or sensitive information. This data is made using algorithms that learn from actual data, allowing companies to create large amounts of data for testing and analysis.

Why is Synthetic Data Important?

1. Privacy Protection: Researchers can use Synthetic Data without violating privacy laws like GDPR in Europe or POPIA in South Africa.
2. Cost and Availability: It solves the problem of not having enough real data and reduces the high costs of collecting it.
3. Wide Applications: It is useful in many fields, such as healthcare, finance, automotive, cybersecurity, and insurance. For example, in healthcare, it helps develop AI tools for diagnosis without compromising patient confidentiality.

Addressing AI and Copyright Issues

Using real-world data to train AI often involves copyrighted material, leading to legal issues. High-profile cases, like The New York Times suing OpenAI and Microsoft, highlight these problems. Synthetic Data can help avoid some copyright issues by creating new data from copyrighted materials, but it doesn’t solve all problems.

Ongoing Challenges and Solutions

1. Legal Risks: Synthetic Data reduces but does not eliminate legal risks of copyright infringement. AI-generated outputs might still infringe on copyright without direct replication.
2. Regulations: The European Union’s AI Act requires disclosure of copyrighted materials used in AI training, promoting transparency. This model could be adopted in South Africa and other regions.

While Synthetic Data offers solutions for privacy and aids AI development, it isn’t a complete fix for copyright challenges. Combining innovative technologies like Synthetic Data with strong regulations is essential for progress and legal compliance.